Research Article
BibTex RIS Cite

Seralar için Tam Otomatik IoT Tabanlı Sulama Sistemi Tasarımı

Year 2022, Volume: 37 Issue: 3, 699 - 706, 17.10.2022
https://doi.org/10.21605/cukurovaumfd.1190306

Abstract

Türkiye, topraklarında tarım yapma potansiyeli yüksek bir ülkedir. Tarımsal çıktı almak için sulama bir ihtiyaçtır. Optimal sulama ile ürün verimi artırılır. Bu çalışmada, seralar için Nesnelerin İnterneti tabanlı bir yaklaşımla tam otomatik bir sulama sistemi tasarlandı. 10HS toprak nemi ve pt1000 sıcaklık sensörlerini kullanan sistem yardımıyla, sulamaya dayalı karar sistemi oluşturularak, bitkilerin optimum sulama alması sağlandı. Evapotranspirasyon denetleyici tabanlı sulamaya kıyasla 25 ton/dönüm su tasarrufu elde edildi. Sistem çevrimiçi çalışır ve iki çalışma moduna sahip olarak tasarlandı: tam otomatik ve manuel. Tam otomatik sistem, su israfını ve işçilik maliyetlerini azaltarak tasarruf elde edildi. Modlar arasında geçiş, bir mobil uygulama tasarlanarak gerçekleştirildi ve sistemin parametreleri bulut hizmetleri aracılığıyla iletişim kurdu.

References

  • 1. Miorandi, D., Sicari, S., Pellegrini, F., Chlamtac, I., 2017. Internet of Things: Vision, Application Areas and Research Challenges. 978-1-5090-3243-3/17.
  • 2. Eriş, H., Çevik, U., 2019. Implementation of Target Tracking Methods on Images Taken from Unmanned Aerial Vehicles. IEEE 17th World Symposium on Applied Machine Intelligence and Informatics (SAMI), 311-316, doi: 10.1109/SAMI.2019.8782768.
  • 3. Anisha, A., Menon, R.A., Prabhakar, A., 2017. Electronically Controlled Water Flow Restrictor to Limit the Domestic Wastage of Water, 978-1-5386-1716-8/17.
  • 4. Ullo, S.L., Sinha, G.R., 2020. Advances in Smart Environment Monitoring Systems Using IoT and Sensors (Basel, Switzerland) 20, 11 3113. 31 May 2020, doi:10.3390/s20113113.
  • 5. Ingelrest, F., Barrenetxea, G., Schaefer, G., Vetterli, M., Couach, O., Parlange, M., 2010. SensorScope: Application-Specific Sensor Network for Environmental Monitoring. ACM Transactions on Sensor Networks (TOSN), 6(2). 6. Manoharan, A.M., Rathinasabapathy, V., 2018. Smart Water Quality Monitoring and Metering Using Lora for Smart Villages. 2nd International Conference on Smart Grid and Smart Cities (ICSGSC), 57-61, doi:10.1109/ ICSGSC.018.8541336.
  • 7. Shelestov, A., 2018. Air Quality Monitoring in Urban Areas Using in-situ and Satellite Data Within Era-planet Project. IGARSS 2018- 2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain, 1668-1671, doi: 10.1109/IGARSS.2018. 8518368.
  • 8. Sharma, J., John, S., 2017. Real Time Ambient Air Quality Monitoring System Using Sensor Technology. Int. J. Adv. Mech. Civ. Eng. 4, 72–73.
  • 9. The European Network of Observing Our Changing Planet, url: http://www.era-planet.eu, Last Accessed: 11.08.2022, 2015, Italy.
  • 10. Croce, D., Gucciardo, M., Mangione, S., Santaromita, G., Tinnirello, I., 2020. Lora Technology Demystified: from Link Behavior to Cell-Level Performance. IEEE Transactions on Wireless Communications, 19(2).
  • 11. Darmono, H., Perdana, R., Puspitasari, W., 2020. Observation of Greenhouse Condition Based on Wireless Sensor Networks. The 1st Annual Technology, Applied Science and Engineering Conference, IOP Conf. Series: Materials Science and Engineering 732, 012107, doi:10.1088/1757-899X/732/1/012107.
  • 12. Sa-Ingthong, J., Phonphoem, A., Jansang, A., Jaikaeo, C., 2021. Probabilistic Analysis and Optimization of Packet Losses in Dense LoRa Networks, SN Computer Science (2022) 3, 25, https://doi.org/10.1007/s42979-021-00883-3.
  • 13. Celiktopuz, E., Kapur, B., Sarıdas, M.A., Paydas Kargı, S., 2020. Response of Strawberry Fruit and Leaf Nutrient Concentrations to the Application of Irrigation Levels and A Biostimulant. Journal of Plant Nutrition, doi:10.1080/01904167.2020.1806310.
  • 14. Angelopoulos, C.M., Filios, G., Nikoletseas, S., Raptis, T.P., 2020. Keeping Data at the Edge of Smart Irrigation Networks: A Case Study in Strawberry Greenhouses. Computer Networks, 167, 107039. 15. Ko, A., Mascaro, G., Vivoni, E.R., 2016. Irrigation Impacts on Scaling Properties of Soil Moisture and the Calibration of a Multifractal Downscaling Model. IEEE Trans. Geoscience Remote Sensing, 54(6), 3128-3142.
  • 16. Roopaei, M., Rad, P., Choo, K.K.R., 2017. Cloud of Things in Smart Agriculture: Intelligent Irrigation Monitoring by Thermal Imaging. IEEE Computer Society, 2325- 6095/17.
  • 17. McCready, M.S., Dukes, M.D., Miller, G.L., 2009. Water Conservation Potential of Smart Irrigation Controllers on St. Augustinegrass. Agric. Water Management, 96(11), 1623–1632.
  • 18. Cardenas-Lailhacar, B., Dukes, M.D., Miller, G.L., 2005. Sensor Based Control of Irrigation in Bermudagrass. ASAE Paper No: 052180, St. Joseph, MI.
  • 19. Haley, M.D., Dukes, M.D., Miller, G.L., 2007. Residential Water Use in Central Florida. J. Irrig. Drain. Eng., 133(5), 427–434.
  • 20. Grabow, G.L., Vasanth, A., Huffman, R.L., Miller, G.L., 2008. Evaluation of Evapotranspiration and Soil Moisture-Based Irrigation Control on Turfgrass. Proc. ASCE EWRI World Environmental and Water Resources Congress, ASCE, Reston, VA.

A Design of Fully Automated Irrigation System IoT-Based Approach for Greenhouses

Year 2022, Volume: 37 Issue: 3, 699 - 706, 17.10.2022
https://doi.org/10.21605/cukurovaumfd.1190306

Abstract

Turkey is a country with a high potential for agriculture purposes. Irrigation is a need to receive agricultural output. Crop yield increases with optimal irrigation. Therefore, this work has designed a fully automated irrigation system with an IoT-based approach for greenhouses. Using 10HS soil moisture and pt1000 temperature sensors, the system has successfully generated irrigation-based decisions and saved 25 tons/da water compared to Et (Evapotranspiration) controller-based irrigation while plants received optimal irrigation. The system works online and has two operation modes: fully automated and manual. Fully automated system decreased water-wastages and labouring costs. Switching between modes can be operated using a mobile application and parameters of the system communicates via cloud services.

References

  • 1. Miorandi, D., Sicari, S., Pellegrini, F., Chlamtac, I., 2017. Internet of Things: Vision, Application Areas and Research Challenges. 978-1-5090-3243-3/17.
  • 2. Eriş, H., Çevik, U., 2019. Implementation of Target Tracking Methods on Images Taken from Unmanned Aerial Vehicles. IEEE 17th World Symposium on Applied Machine Intelligence and Informatics (SAMI), 311-316, doi: 10.1109/SAMI.2019.8782768.
  • 3. Anisha, A., Menon, R.A., Prabhakar, A., 2017. Electronically Controlled Water Flow Restrictor to Limit the Domestic Wastage of Water, 978-1-5386-1716-8/17.
  • 4. Ullo, S.L., Sinha, G.R., 2020. Advances in Smart Environment Monitoring Systems Using IoT and Sensors (Basel, Switzerland) 20, 11 3113. 31 May 2020, doi:10.3390/s20113113.
  • 5. Ingelrest, F., Barrenetxea, G., Schaefer, G., Vetterli, M., Couach, O., Parlange, M., 2010. SensorScope: Application-Specific Sensor Network for Environmental Monitoring. ACM Transactions on Sensor Networks (TOSN), 6(2). 6. Manoharan, A.M., Rathinasabapathy, V., 2018. Smart Water Quality Monitoring and Metering Using Lora for Smart Villages. 2nd International Conference on Smart Grid and Smart Cities (ICSGSC), 57-61, doi:10.1109/ ICSGSC.018.8541336.
  • 7. Shelestov, A., 2018. Air Quality Monitoring in Urban Areas Using in-situ and Satellite Data Within Era-planet Project. IGARSS 2018- 2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain, 1668-1671, doi: 10.1109/IGARSS.2018. 8518368.
  • 8. Sharma, J., John, S., 2017. Real Time Ambient Air Quality Monitoring System Using Sensor Technology. Int. J. Adv. Mech. Civ. Eng. 4, 72–73.
  • 9. The European Network of Observing Our Changing Planet, url: http://www.era-planet.eu, Last Accessed: 11.08.2022, 2015, Italy.
  • 10. Croce, D., Gucciardo, M., Mangione, S., Santaromita, G., Tinnirello, I., 2020. Lora Technology Demystified: from Link Behavior to Cell-Level Performance. IEEE Transactions on Wireless Communications, 19(2).
  • 11. Darmono, H., Perdana, R., Puspitasari, W., 2020. Observation of Greenhouse Condition Based on Wireless Sensor Networks. The 1st Annual Technology, Applied Science and Engineering Conference, IOP Conf. Series: Materials Science and Engineering 732, 012107, doi:10.1088/1757-899X/732/1/012107.
  • 12. Sa-Ingthong, J., Phonphoem, A., Jansang, A., Jaikaeo, C., 2021. Probabilistic Analysis and Optimization of Packet Losses in Dense LoRa Networks, SN Computer Science (2022) 3, 25, https://doi.org/10.1007/s42979-021-00883-3.
  • 13. Celiktopuz, E., Kapur, B., Sarıdas, M.A., Paydas Kargı, S., 2020. Response of Strawberry Fruit and Leaf Nutrient Concentrations to the Application of Irrigation Levels and A Biostimulant. Journal of Plant Nutrition, doi:10.1080/01904167.2020.1806310.
  • 14. Angelopoulos, C.M., Filios, G., Nikoletseas, S., Raptis, T.P., 2020. Keeping Data at the Edge of Smart Irrigation Networks: A Case Study in Strawberry Greenhouses. Computer Networks, 167, 107039. 15. Ko, A., Mascaro, G., Vivoni, E.R., 2016. Irrigation Impacts on Scaling Properties of Soil Moisture and the Calibration of a Multifractal Downscaling Model. IEEE Trans. Geoscience Remote Sensing, 54(6), 3128-3142.
  • 16. Roopaei, M., Rad, P., Choo, K.K.R., 2017. Cloud of Things in Smart Agriculture: Intelligent Irrigation Monitoring by Thermal Imaging. IEEE Computer Society, 2325- 6095/17.
  • 17. McCready, M.S., Dukes, M.D., Miller, G.L., 2009. Water Conservation Potential of Smart Irrigation Controllers on St. Augustinegrass. Agric. Water Management, 96(11), 1623–1632.
  • 18. Cardenas-Lailhacar, B., Dukes, M.D., Miller, G.L., 2005. Sensor Based Control of Irrigation in Bermudagrass. ASAE Paper No: 052180, St. Joseph, MI.
  • 19. Haley, M.D., Dukes, M.D., Miller, G.L., 2007. Residential Water Use in Central Florida. J. Irrig. Drain. Eng., 133(5), 427–434.
  • 20. Grabow, G.L., Vasanth, A., Huffman, R.L., Miller, G.L., 2008. Evaluation of Evapotranspiration and Soil Moisture-Based Irrigation Control on Turfgrass. Proc. ASCE EWRI World Environmental and Water Resources Congress, ASCE, Reston, VA.
There are 18 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

Halit Eriş This is me 0000-0002-2384-5052

Eser Çeliktopuz This is me 0000-0002-5355-1717

Ulus Çevik This is me 0000-0002-0956-9725

Burçak Kapur This is me 0000-0001-6131-4458

Publication Date October 17, 2022
Published in Issue Year 2022 Volume: 37 Issue: 3

Cite

APA Eriş, H., Çeliktopuz, E., Çevik, U., Kapur, B. (2022). A Design of Fully Automated Irrigation System IoT-Based Approach for Greenhouses. Çukurova Üniversitesi Mühendislik Fakültesi Dergisi, 37(3), 699-706. https://doi.org/10.21605/cukurovaumfd.1190306